AI Technical Due Diligence Services
Expert evaluation for high-stakes AI investments
Unlock the true value of AI investments
In the rapidly evolving AI landscape, technical due diligence is no longer optional—it's essential. Our specialized AI Due Diligence service helps venture capital firms, private equity investors, and strategic acquirers validate technical claims, identify hidden risks, and make confident investment decisions.
Why AI Investments Require Specialized Due Diligence
Beyond the Demo: Uncovering Technical Reality
AI companies present unique due diligence challenges. Impressive demos may mask fundamental technical issues that only become apparent after investment. Our specialized methodology uncovers the technical reality behind the pitch deck.
The Hidden Risks in AI Investments:
Technical Debt Invisibility
Underlying implementation issues masked by polished demos
Data Dependency Risks
Long-term performance tied to data quality and acquisition costs
Scaling Economics Surprises
Infrastructure costs that grow non-linearly with usage
Competitive Vulnerability
Undifferentiated technology easily replicated by competitors
Integration Complexity
Underestimated technical challenges leading to failed acquisitions
Regulatory Compliance Gaps
Emerging AI regulations that can impact product viability and go-to-market timelines
Our Comprehensive AI Due Diligence Approach
Model Architecture & Innovation
We evaluate the true innovation in a company's AI approach, distinguishing proprietary advances from commodity techniques.
- Foundation model selection and customization strategy
- Architecture decisions and performance trade-offs
- Parameter efficiency and computational requirements
- Technical differentiation from competitors
- Future adaptability as AI technology evolves
Data Strategy & Governance
We validate the company's data foundation—often the true source of competitive advantage in AI.
- Data acquisition methods and sustainability
- Quality assurance and preprocessing approaches
- Bias identification and mitigation strategies
- Compliance with privacy regulations and ethical standards
- Data moats and defensive advantages
Infrastructure & Scaling Economics
We analyze how technical architecture decisions impact business economics at scale.
- Training infrastructure efficiency and cost structure
- Inference optimization and serving architecture
- Performance/cost trade-offs and bottlenecks
- Horizontal scaling capabilities
- Technical factors affecting unit economics
Trust, Safety & Reliability
We identify hidden risks in model behavior, safety mechanisms, and operational reliability.
- Output filtering and content moderation approaches
- Explainability and interpretability measures
- Failure mode analysis and graceful degradation
- Security vulnerabilities and attack vectors
- Compliance with emerging AI regulations
Engineering Quality & Execution
We assess the team's ability to execute on technical promises and manage complexity.
- Development practices and technical debt management
- Engineering team structure and expertise gaps
- Documentation quality and knowledge management
- DevOps maturity and deployment practices
- Technical leadership and decision-making processes
Talent & Organizational Structure
We evaluate the team composition, leadership capabilities, and organizational design to assess execution potential.
- Leadership team assessment and technical credibility
- Organizational structure and reporting relationships
- Talent acquisition and retention strategies
- Team composition and skill gap analysis
- Knowledge sharing and collaboration frameworks
Our Proven Process
Our structured 4-week methodology provides comprehensive technical insight with minimal disruption to the target company.
Preparation & Discovery
- Initial consultation to understand investment thesis
- Customized questionnaire development
- Documentation collection and preliminary analysis
- Interview scheduling with key technical personnel
Technical Deep Dive
- Structured interviews with technical leadership
- Architecture and infrastructure evaluation
- Data strategy and governance assessment
- Engineering practices and team capabilities analysis
Analysis & Business Evaluation
- Synthesis of technical findings
- Connection of technical factors to business metrics
- Competitive positioning assessment
- Risk identification and prioritization
Reporting & Presentation
- Comprehensive due diligence report development
- Investment committee presentation preparation
- Findings review and recommendation finalization
- Technical KPI framework for post-investment monitoring
Deliverables That Drive Decision Making
Comprehensive Due Diligence Report
A detailed assessment across all technical dimensions, connecting findings to investment implications.
Risk Assessment Matrix
Prioritized technical risks with clear mitigation strategies and impact analysis.
Technical Valuation Analysis
How technical strengths and weaknesses should impact valuation and deal structure.
Integration Roadmap
For acquisitions, a technical blueprint for successful post-transaction integration.
Technical KPI Framework
Key metrics to monitor post-investment to track technical progress and health.
Competitive Landscape Analysis
Detailed technical comparison with competitors and assessment of market positioning.
Our Team
Meet the experts behind our AI due diligence services
Dr. Sarah Chen
Chief AI Officer
Former ML Research Lead at Google with 15+ years of experience in AI systems and 30+ published papers. PhD in Computer Science from Stanford.
Michael Rodriguez
Technical Due Diligence Lead
Ex-CTO of an acquired AI startup with deep expertise in scaling ML infrastructure. Previously led technical assessments for 20+ acquisitions.
Jennifer Park
Data Strategy Expert
Former Head of Data Science at a Fortune 100 company. Specializes in data quality assessment and governance frameworks for AI systems.
David Okonkwo
AI Ethics Specialist
Published author on responsible AI development with experience advising government agencies on AI regulation and compliance frameworks.
Alex Thompson
ML Infrastructure Analyst
Cloud architecture expert specializing in ML infrastructure optimization. Previously led ML platform teams at AWS and high-growth startups.
Priya Sharma
Investment Advisor
Former VC partner with expertise in AI investments. Has evaluated 100+ AI startups and helped structure technical milestones for funding rounds.
Our Team's Expertise
Our team brings together deep expertise in:
Machine Learning & AI Development: Firsthand experience building and scaling AI systems
Data Science & Engineering: Practical knowledge of data infrastructure and governance
Technical Leadership: Experience guiding engineering teams in high-growth environments
Investment Due Diligence: Understanding of VC and PE investment processes
M&A Integration: Experience with successful post-acquisition technical integration
AI Ethics & Governance: Expertise in responsible AI development and regulatory compliance
Engagement Options
We offer flexible service levels to meet your specific needs:
Standard Assessment
$15,000-$25,000
- Customized questionnaire
- 5-6 technical interviews
- Comprehensive report
- Investment committee presentation
- 4-week timeline
Comprehensive Evaluation
$30,000-$50,000
- In-depth code reviews
- Data quality assessment
- Infrastructure validation
- Security testing
- Extended engineering interviews
- Detailed integration planning
- 5-6 week timeline
Custom Programs
Contact for Pricing
- For firms with ongoing AI investment strategies
- Portfolio-wide programs
- Preferential pricing
- Customized to your specific needs
Frequently Asked Questions
How is your AI due diligence different from general technical due diligence?
Traditional technical due diligence often misses AI-specific challenges like data quality assessment, model architecture evaluation, and scaling economics particular to machine learning systems. Our methodology is purpose-built for AI companies.
How disruptive is your process to the target company?
We've designed our process to be minimally disruptive. Our structured questionnaire approach means we only require 5-6 hours of interview time spread across key technical leaders.
Can you adjust the timeline for urgent deals?
Yes, we offer accelerated timelines for time-sensitive opportunities, though we recommend the standard 4-week process for optimal depth of analysis.
Do you work with companies at specific stages?
We've developed specialized methodologies for companies from Seed through Series C, as well as for mature companies being acquired. Each stage presents unique technical due diligence challenges.
How do you handle highly technical or specialized AI approaches?
Our team includes experts across various AI domains including computer vision, NLP, reinforcement learning, and generative AI. For highly specialized domains, we can also engage domain experts from our network.
Do you provide ongoing technical advisory after the investment?
Yes, we offer post-investment technical advisory services to help monitor the implementation of our recommendations and provide guidance as the company scales its AI capabilities.
Get Started
Ready to derisk your next AI investment? Schedule a consultation to discuss your specific needs.